如何在R语言的同一张图中标注两个回归方程？

方法一：使用ggpmisc包（推荐，操作简便） #

先安装并加载ggpmisc包，它可以自动拟合回归并生成标准格式的方程标签：

# 首次使用时安装包
install.packages("ggpmisc")
library(ggpmisc)

修改你原有的ggplot代码，添加stat_poly_eq层即可自动为每组生成y=mx+c形式的方程及R²值：

ggplot(data=Test, aes(x=Year, y=Value, color = Factor)) + 
    geom_point(size=2, shape=22) + 
    geom_smooth(method='lm', se=FALSE) # 可选去掉置信区间，简化图表
    scale_y_continuous(breaks=c(1,50, 100, 150, 200, 250, 300, 365)) +
    scale_x_continuous(breaks = Test$Year) +
    # 添加回归方程和R²标签
    stat_poly_eq(
        aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~")),
        formula = y ~ x,
        parse = TRUE,
        size = 4,
        position = position_dodge(width = 0.5) # 避免两组标签重叠
    ) +
    theme(axis.text.x = 
          element_text(color = "grey20", size = 10, angle = 0, 
                       hjust = .5, vjust = .5, face = "bold"),
        axis.text.y = 
          element_text(color = "grey20", size = 10, angle = 0, 
                       hjust = .5, vjust = .5, face = "bold"))

参数说明：

• ..eq.label..对应回归方程，..rr.label..对应R²值，用~~~~分隔可让两者同行显示，换成\n则会换行
• parse=TRUE让ggplot解析数学表达式，正确渲染方程格式
• position_dodge的宽度可根据你的数据调整，确保标签不重叠

方法二：手动计算参数后添加标签（无需额外包） #

如果不想安装新包，可通过dplyr分组计算回归系数，再手动生成标签：

library(dplyr)

# 按Factor分组计算回归方程参数
eq_labels <- Test %>%
    group_by(Factor) %>%
    summarise(
        model = list(lm(Value ~ Year)),
        slope = coef(model[[1]])[["Year"]],
        intercept = coef(model[[1]])[["(Intercept)"]],
        # 生成保留两位小数的y=mx+c格式标签
        eq_label = paste0("y = ", round(slope, 2), "x + ", round(intercept, 2))
    )

# 绘制图表并添加自定义标签
ggplot(data=Test, aes(x=Year, y=Value, color = Factor)) + 
    geom_point(size=2, shape=22) + 
    geom_smooth(method='lm') +
    scale_y_continuous(breaks=c(1,50, 100, 150, 200, 250, 300, 365)) +
    scale_x_continuous(breaks = Test$Year) +
    # 将标签放在每组数据的右上方
    geom_text(
        data = eq_labels,
        aes(x = max(Test$Year), y = predict(model[[1]], newdata = data.frame(Year = max(Test$Year))),
            label = eq_label, color = Factor),
        hjust = 1.1,
        size = 4,
        fontface = "bold"
    ) +
    theme(axis.text.x = 
          element_text(color = "grey20", size = 10, angle = 0, 
                       hjust = .5, vjust = .5, face = "bold"),
        axis.text.y = 
          element_text(color = "grey20", size = 10, angle = 0, 
                       hjust = .5, vjust = .5, face = "bold"))

这种方法能完全自定义标签的位置和格式，适合需要精细化调整的场景。

内容的提问来源于stack exchange，提问作者Rahul